Pasquini, Stephanie M. MSPT1; Peterson, Melissa L. PhD, PT2; Rattansi, Saira M. BSPT1; Colclasure, Kimberly MPT1; King, Darvis DPT1; Mergen, Angela BSPT1; Ropp, Christina DPT1; Vaughn, Jamie MSPT1
The number of total knee replacement (TKR) surgeries is on the rise, with more than 431 000 individuals undergoing such surgery in the United States in 2004.1 Following surgery, an assistive device is prescribed to decrease weight bearing on the involved limb as well as to provide stability. In our experience, individuals have typically been instructed in the use of a standard walker postoperatively on the basis of a general perception that a standard walker provides greater stability and weight-bearing support than a wheeled walker. However, in recent years, wheeled walkers have been more commonly recommended on the basis of their proposed potential contribution to natural, continuous gait.2
While several studies have been published describing gait parameters following TKR, no studies have reported the role that assistive device prescription plays on gait parameters, such as velocity, endurance, and overall safety in this population. However, in other patient populations, such as older adults with gait disorders and individuals with Parkinson's disease, faster gait speed and greater endurance have been reported when using a wheeled walker than with a standard walker.3,4 In a study of healthy older adults, cardiac and respiratory demands were lower when using a wheeled walker than with a standard walker, as measured by changes in heart rate, blood pressure, oxygen consumption, and subjective rating of exertion.5 Gait variability is also used to estimate an individual's safety. Several studies have reported associations between large amounts of variability in gait, such as asymmetrical step length and width, and higher fall risk in older adults.6,7,8
The question is whether there are possible advantages to using a wheeled walker instead of a standard walker post–knee replacement. The purpose of this study was to investigate the potential differences in gait, including velocity, step length, cadence, and endurance, in individuals following a TKR on the basis of the prescription of a standard walker versus a wheeled walker. It was hypothesized that individuals using a wheeled walker would be able to walk with greater velocity, longer step lengths, and for a greater distance than those using a standard walker.
An institutional review board approved, nonequivalent pretest-posttest control group design study was conducted using a convenience sample. Since patients in this particular setting have historically been prescribed a standard walker following TKR, this assistive device was considered the control condition and the use of a wheeled walker was considered the experimental condition. All participants provided written informed consent prior to inclusion in the study. All participants were treated according to a standardized physical therapy treatment protocol after TKR. Data were collected preoperatively, prior to discharge from acute care setting, and at 6 weeks postoperatively by an investigator not involved in the participant's treatment sessions.
In the preoperative phase, informed consent, the Lower Extremity Functional Scale (LEFS),9 bilateral lower extremity range of motion (ROM), and bilateral strength testing were completed. The 2 postoperative data collection phases each included the ROM and strength measures, as well as a standardized measure of both perceived exertion and various gait parameters. Data collection took approximately 30 minutes to complete for each phase.
Setting and Participants
The study was conducted at a 600-bed, level 1 trauma center in Peoria, Illinois, between April 2007 and June 2008. Current practice with the orthopedic surgeons at this facility reflects a preference to use a standard walker after total joint replacement. The sample used for the project was drawn from individuals who were having an elective single TKR by 1 of 2 participating orthopedic surgeons, attended an informational preoperative clinic, and required the use of a walker postoperatively. Participants were excluded if they were having a revision, bilateral, or unicompartmental knee replacements, weighed more than 300 lb, were younger than 40 years or older than 80 years, required any walker modifications, used a wheelchair or walker for more than half of their mobility requirements prior to surgery, or did not comprehend simple instructions in English.
Preoperatively, 87 participants gave consent and were enrolled in the study. Once each participant had undergone a TKR and a physical therapy referral was received, the research subject coordinator assigned the participant into either a front-wheeled walker group (n = 38) or a standard walker group (n = 32). Although none of the participants required an assistive device prior to surgery for more than incidental mobility such as walking long distances, painful days, or uneven surfaces, some of the participants had already procured a walker in anticipation of the surgery. In these cases, group assignment was made according to the walker already owned. Those participants arriving for surgery without a walker were randomly assigned into a walker group. Those in the control group were instructed in the use of a standard walker for all gait training sessions, whereas those in the experimental group were instructed in the use of a wheeled walker for all gait training sessions. Figure 1 shows a flowchart of the recruitment, randomization, and follow-up process.
The total joint preoperative clinic investigators received a training session regarding inclusion criteria, informed consent, data collection, and necessary documentation. Therapists treating study participants completed training on the physical therapy treatment protocol. Assigned data collectors completed training for standardized use of the GAITRite system (GAITRite Gold System; MAP/CIR, Inc, Havertown, Pennsylvania), Six Minute Walk Test (6MWT),10,11 Borg CR10 scale (Borg Products USA, Inc, Atlanta, Georgia),12 and ROM and strength testing.
All study participants received physical therapy from a standardized protocol of twice-daily treatment sessions of 30 to 45 minutes each. The participants worked through a gradual progression of protocol exercises of 10 to 20 repetitions including ankle pumps, quadriceps sets, heel slides, hip abduction/adduction, short and long arc quadriceps, straight leg raises, and stretching. The participants also received bed mobility, transfer, gait, stair, and safety training with the assigned walker and weight bearing as tolerated on the surgical extremity. Participants were asked to report any falls that had occurred during stay at the acute care setting. Data collection was completed just prior to discharge from the acute care setting.
The research subject coordinator scheduled the 6-week data collection appointment near the participant's 6-week follow-up appointment with the orthopedic surgeon. This session included all measures taken prior to discharge from the acute care setting as well as a brief patient self-report to determine length of time using the assistive device and number of falls since surgery. An LEFS was also completed at this time to compare with preoperative data.
Primary Outcome Measures
All measures were completed prior to discharge from the acute care setting and 6-week follow-up session. Distance walked was measured by the 6MWT, which is a commonly used performance-based test to measure the distance a person can walk at a comfortable pace on a flat, hard surface for 6 minutes.10,11 Participants were allowed to rest, if needed, but were instructed to resume walking as soon as they were able to do so. The participants walked on an 18.39-m premeasured, tiled, indoor corridor. All participants used the walker designated to them during the acute care data collection session, whereas only those participants still requiring a device used it at the 6-week follow-up session. Subjects wore skid-resistant shoes and gait belt and were supervised by the data collector. Encouragement has been found to improve performance; therefore, standardized encouragements of “you are doing well” and “keep up the good work” were given every minute according to a script.13 At the end of 6 minutes, the distance walked and the number and duration of rest breaks were recorded. A previous study reported test-retest reliability coefficients of 0.94 and the minimal detectable change at the 90% confidence level was 61.34 m in patients with osteoarthritis and status post-TKA.14
The Borg CR10 scale was utilized at the end of the 6MWT as a psychophysical self-rating scale to provide an index of the participants' perceived exertion. The scale and instructions were presented to the participants prior to the 6MWT in order to familiarize themselves and allow them a chance to ask questions. This scale was used with permission, according to the exact design and instructions created by Borg.12 They were then shown the Borg CR10 scale again immediately after the 6MWT and asked to rate their perceived exertion. Previous reports of rating of perceived exertion correlated linearly with heart rate and work intensity, with correlation coefficients ranging from 0.80 to 0.90.15
The GAITRite walkway system was used to collect and analyze spatial and temporal gait parameters including gait speed, cadence, step length of the involved extremity, step length of the uninvolved extremity, and the step length differential. Step length differential assesses symmetry between the lengths of the steps taken by the 2 extremities, with a smaller value indicating greater symmetry. The walkway was a 4.27 m (length) ÷ 0.61 m (breadth) ÷ 0.32-cm (height) rubberized carpet secured to the floor. The carpet contains more than 13 000 pressure-sensitive electrodes that map the geometry of each footfall as the individual walks across the carpet.16 Software is then used to calculate the spatial and temporal parameters from these footprints. Participants were asked to walk the length of the walkway by using the assigned assistive device for a series of 3 trials. The GAITRite system has demonstrated strong validity for assessing step parameters of gait following TKR in older adults.17 In this study, the scores of the GAITRite system, when compared with a 3-dimensional motion analysis system, achieved intraclass correlation coefficients ranging from 0.92 to 0.99 when comparing velocity, cadence, step length, and step time.17
Secondary Outcome Measures
Participants filled out the LEFS when they provided informed consent at the preoperative clinic and again 6 weeks after surgery. It was not completed during stay at the acute care setting because of the significant functional limitations expected as a result of the surgery. The LEFS is a self-report functional status measure for lower extremity musculoskeletal conditions.9 Twenty items are scored on a 5-point scale, with zero representing “extreme difficulty” to 4 representing “no difficulty.” Cross-sectional validity correlation coefficients have shown statistically significant correlations (0.44–0.51) between LEFS and the Timed Up and Go test, Timed Stairs, functional independence measure for ambulation, and 6MWT.18
Six weeks after surgery, patients self-reported falls and walker use by answering the questions: “How many falls have you had since surgery?” and “How many days after surgery did you use your walker?” These questions were asked to determine whether the walker type was related to fall frequency or the amount of time the participant needed a walker for ambulation.
During pre- and postsurgery data collection periods, bilateral lower extremity active range of motion (AROM) and strength were tested in sitting and supine. Knee flexion and extension AROM was collected using a 30.48-cm goniometer (JAMAR goniometer; HOSPEO, Inc; Miami, Florida).19 Strength of the bilateral tibialis anterior, quadriceps, and iliopsoas muscles was evaluated with manual muscle testing by accepted handling positions.20 These measures were taken only to ensure that the groups were similar with respect to ROM and strength.
All data analyses were performed with SPSS for Windows, Version 15.0 (SPSS, Inc, Chicago, Illinois). Descriptive data analysis was followed by a repeated-measures 2 ÷ 2 mixed-model multivariate analysis of variance (MANOVA) with an α level of .05 for the subset of 51 participants who completed all data collection phases. The independent variables for the MANOVA were group (with 2 levels) and time (with 2 levels). The dependent variables for gait assessment were velocity, step length of the involved extremity, step length of the noninvolved extremity, cadence, and the step length differential. Subsequent 2 ÷ 2 mixed-model univariate analyses of variance (ANOVAs) were performed for each dependent variable (6MWT, Borg CR10 scale, and LEFS score), using a Bonferroni-corrected α level of .01. The 6MWT and CR10 scale repeated-measures comparisons were made between discharge from the acute care setting and 6-week follow-up; and the LEFS repeated-measures comparisons were made between preoperative reports and 6-week follow-up. A chi-square analysis was performed to determine whether there was a relationship between walker type and ability to achieve household ambulation gait speed by discharge from the acute care setting.
To ensure that the 2 walker groups were similar prior to surgery, independent t tests were used to compare baseline information collected at the preoperative clinic, including age, LEFS score, and operative knee extension. In addition, t tests were also used to compare the same baseline data between the subgroups comprising those individuals whose walker assignment was random compared with those whose group assignment was self-selected. For example, within the wheeled walker group, baseline comparisons were made between those assigned a wheeled walker and those assigned to the group because a wheeled walker already had been acquired.
A completer analysis was used rather than an intent-to-treat model.21 Because large differences between data both at discharge from the acute care setting and at 6-week follow-up were expected, the investigators did not feel that carrying data collection at discharge from the acute care setting over for those not completing data collection at the 6-week follow-up would provide an accurate representation of the sample. Therefore, only those participants completing all data collection periods were included in the analysis.
Of the 87 participants initially enrolled in the study, 23 participants in the standard walker group and 28 participants in the wheeled walker group completed all data collection phases. Table 1 displays the key characteristics of the subjects who completed all phases of the study. Figure 1 provides a flow diagram listing participant reasons for dropping out of the study before assessment session 2. The final participant totals reflect an overall dropout rate of 41%. Table 2 provides a comparison of the baseline characteristics for those completing assessment session 2 and those who did not complete this session.
While the original design called for random assignment to groups, nearly 70% of the participants had already purchased a walker before undergoing surgery. Twenty of 32 participants in the standard walker group (62.5%) and 32 of 38 in the wheeled walker (84.2%) were assigned to a group on the basis of a previously purchased device. However, to be included in the study, participants must not have relied on a wheelchair or walker for more than incidental mobility, such as long distances, uneven surfaces, or exacerbation of pain.
Preliminary Group Comparisons
For those participants completing both phases of the study, independent t tests revealed the 2 groups to be similar prior to surgery, with regard to age and scores on the LEFS (see Table 1). Results of a Mann-Whitney U test for quadriceps, iliopsoas, and anterior tibialis muscle strength on the operative side revealed no differences between the groups (P > .5). Following surgery, all ROM and strength measures between the 2 walker groups were statistically equivalent (P > .4). The participants who failed to return for the 6-week follow-up session (noncompleters) appeared to differ from the participants completing the study for a number of variables, including velocity, cadence, and walking endurance. At discharge from the acute care setting, noncompleters in the standard walker group walked slower than completers in the wheeled walker group (P = .01) and with a slower cadence than both wheeled walker groups (completers: P = .004; and noncompleters: P = .007) (see Table 2).
To ensure equivalence among participants with and without random group assignment, t tests were used to compare preoperative LEFS scores, as well as acute care gait data (step length, velocity, cadence, step-length differential, and 6MWT) between individuals with random assignment and those without random assignment within each walker group. There were no significant differences between these subgroups for any variable (P > .3).
Spatiotemporal Gait Measures
The results of the repeated-measures MANOVA for gait variables revealed a significant main effect both for time (F = 123.9; df = 5, 45; P < .001) and for walker type (F = 2.97; df = 5, 45; P < .02). Testing for an interaction between time and walker type was not significant (P = .06).
For the time variable, follow-up univariate testing resulted in significant differences in both groups between data collection both at discharge from the acute care setting and at 6-week follow-up for all gait variables. Step length on the involved and noninvolved lower extremities, velocity, and cadence increased over the follow-up period, whereas the step length differential decreased (P < .001 for all variables). Table 3 summarizes within-group and between-group across data collection periods for all gait variables.
Table 3Mean SD for G...Image Tools
Univariate tests for walker type revealed differences for velocity (F = 7.7; df = 1, 49; P = .008) and step length on the noninvolved extremity only (F = 10.9; df = 1, 49; P = .002), with individuals in the wheeled walker group walking faster and taking a longer step on the noninvolved side at discharge from the acute care setting.
Chi-square analysis revealed a significant relationship between walker type and ability to achieve household ambulation speed (40 cm/s) by discharge from the acute care setting, χ2(1, N = 69) = 5.77, P = .016. Using a wheeled walker was more likely to result in reaching household ambulation speed, with 24% of the participants in this group meeting this threshold, than in the standard walker group, with less than 1% of participants meeting this threshold.
Repeated-measures ANOVAs for the 6MWT, Borg CR10 scale, and LEFS scores revealed significant main effects for time only. Participants in both groups were able to walk farther during the 6MWT (P < .001) with less perceived exertion (P < .001) for data collection at 6-week follow-up than for data collection at discharge from the acute care setting. In addition, scores on the LEFS test were higher 6 weeks after surgery than just prior to surgery (P = .005). However, there were no significant main effects for walker type, nor were there significant interactions between time and walker type.
Functional outcome measures showed the groups to be very similar across the entire study period. Both groups required 5 to 6 inpatient physical therapy sessions before discharge (P = .4), and both groups reported using an assistive device for approximately 18 days following discharge (P = .9) (see Table 1). At the 6-week follow-up visit, 4 members of the standard group used a straight cane for ambulation compared with 2 members of the wheeled walker group. No participants sustained a fall during the acute care hospitalization, whereas 2 members of the standard walker group and 1 member of the wheeled walker group reported a fall after home discharge (P = .47) (see Table 1). While specific information regarding the use of the walker at the time of the fall was not collected, it was reported that 1 of the individuals within the standard walker group fell because of a defibrillator firing and the 1 fall occurring within the wheeled walker group occurred because of a slip on ice.
In this study, we compared gait performance of individuals following a TKR while using either a standard or a wheeled walker. As the number of individuals electing to undergo knee surgery continues to grow and number of days in the acute care setting continues to shrink, it is important to determine whether one type of assistive device allows individuals to achieve functional gait more effectively and safely.
Because many patients are discharged to their own homes at this point in their recovery, the ability to walk at a faster velocity may enable them to be more independent upon returning home. Perry and colleagues22 used gait speed to classify individuals' walking ability, with gait speed of less than 40 cm/s classified as household ambulation, 40 to 80 cm/s classified as limited community ambulation, and more than 80 cm/s classified as community ambulation. While on average, participants in both groups walked at less than 40 cm/s prior to discharge from the acute care setting, those in the wheeled walker group were discharged home able to walk closer to the community ambulation threshold at 25 cm/s than at 16 cm/s in the standard walker group. Furthermore, there was a relationship between type of walker and ability to achieve household ambulation speed, with more individuals in the wheeled walker group meeting this threshold. Although data regarding activity level were not collected for the current study, if individuals are capable of walking at a faster and smoother pace, they may be more willing to increase their activity level and thus reach a greater level of independence more quickly.
The overall 6-week results exhibited no statistically significant difference between groups in gait characteristics, Borg CR10 scale, LEFS, or number of days to graduate from a walker. These results suggest that the type of walker prescribed immediately after surgery may not have a lasting impact on an individual's walking ability 6 weeks later.
Patients and clinicians may choose a standard walker more frequently because of the perception that it is more stable than a wheeled walker. However, the reported rate of falls between groups prior to discharge and 6 weeks after surgery was found to be statistically equivalent. Fall data for both the acute care stay and the six-week follow-up were collected by asking each participant whether he or she had fallen since surgery. This method does rely on participant recall, which could have been inaccurate. Future studies may be strengthened by including regular follow-up phone calls to participants' homes to inquire about falls. Using falling rate as an outcome measure, the results of the current study suggest that either of two walkers can be used after TKR surgery without safety concerns.
The study has limitations. The final sample size was limited by attrition, with an overall dropout rate of 41% from initial recruitment to 6-week follow-up. At the 6-week posttest session, participants self-reported the number of days spent using a walker after surgery before progressing to a cane or to no-assistive device. Thus, the estimates may be imprecise. In addition, there was no attempt to maintain a “controlled” environment once participants left the acute care environment. A variety of factors such as participation in physical therapy, personal motivation to increased function, and participants' perception of the walker as a valued security or as a hindrance to their ability to move, likely influenced participant decisions to continue or discontinue use of the walker. However, there is no reason to believe that one group had different influences than the other group.
Lack of random assignment to groups was a limitation of this study. The original intent was to assign each participant to a walker group prior to the physical therapy evaluation and data collection period in the acute setting. However, a more than anticipated number of individuals purchased a walker in anticipation of the surgery, with twice as many choosing the wheeled walker over the standard walker. We do not have sufficient data to speculate why patients made the decision they did about the type of walker to purchase. Thus, it is impossible to objectively determine any systematic bias based on self-selection of assistive device. Those who self-selected their assistive device did not differ significantly on any key characteristic from those who were randomly assigned to walker group. This finding, combined with our exclusion criteria of individuals who relied on a walker for mobility on a regular basis, provides some protection against group assignment bias. It would not have been feasible to require participants to purchase another assistive device out-of-pocket had they been assigned to the other group. Furthermore, as this study was not funded, the researchers were unable to provide walkers to participants. Our judgment was that lack of randomization to groups was less of a design threat than would have occurred if only a small percentage of eligible patients chose to participate.
Results showed that the use of a wheeled walker can enable an individual to walk at a faster speed and with longer steps on the uninvolved leg during the initial recovery phase. Anecdotal data collected on the number of falls suggest that a wheeled walker can be used immediately after surgery with the same low level of fall risk as a standard walker. Overall, no long-term differences in gait characteristics, energy conservation, or safety existed between groups, suggesting that both types of walkers may be equally effective for use post-TKR surgery.
The authors thank Drs Richard Driessnack and Brian Ted Maurer for allowing their patients to participate in our study. The authors show appreciation to Janelle Hart, PT, Abigail Duffy, PT, Rebecca Johnson, PT, and Kathleen Koors, PT, for collecting preoperative data from participants at the total joint preoperative clinic. The authors also thank Rebecca Zehr, SPT, Kristin Zeurcher, SPT, Brooke Cook, SPT, and Jamie Fifarek, SPT, for collecting data prior to surgery and participating in data analysis.
Copyright © 2010 the Section on Geriatrics of the American Physical Therapy Association